Transaction records are frequently collected by organizations to perform data analysis. However, the collected transaction records rarely comply with any one standard format. Often, the information in one transaction record may be different from the information in another transaction record.
Transaction records that include location information may be utilized by an organization for many practical applications. Unfortunately, because there is no standardization in transaction records and because many transaction records do not include location information, only a fraction of transaction records (which include location information) may be usable for location-based analysis, decision making, metrics, etc.
In order to maximize the utility of all of the transaction records collected by an organization, a solution is needed to determine the location information of the transactions records that do not include any location information.
Conventional solutions may include individually reviewing and analyzing each transaction record to determine information that may be used to identify the location information of where a transaction occurred. For example, an individual associated with an organization collecting transaction records may review and analyze transaction records one at a time, looking for information such as a street address or a branch identifier associated with the transaction record, which may then be associated with a location. However, such methods are slow, tedious, inefficient, prone to error, and lack practical ways of automation. Conventional automated solutions may rely on strict formatting requirements to determine location information, and may be inflexible and prone to error when analyzing transaction records of many different formats. In such cases, simply changing the order of data may be enough to render these conventional automated methods dysfunctional.
Further, even when location information is included in a transaction record, it is not always complete. For example, the street address in the transaction record may be incomplete and missing information such as city and state, or a transaction record may include a city but no street address. In another example, a branch identifier may be included, but it may be an internal number for the merchant associated with the transaction, which does not easily lead to any location by any form of analysis.
Therefore, a solution is needed to determine location information based on transaction records in order to utilize the transaction records in various practical applications.